Method and system for producing a higher quality electromyographic signal from an electrode array

ABSTRACT

A method and system for producing higher quality electromyogram (EMG) signals utilizes an array of electrodes for sensing a plurality of EMG signals in an electrically active region of a subject&#39;s muscle. A weighting function is applied to the EMG signals to produce weighted signals. This weighting function contains correction features for the relative locations of the center of the electrically active region and the electrodes. The quality of the weighted EMG signals is evaluated, and the weighted signals or sum or mean of the weighted signals whose evaluated quality is insufficient are replaced. A sum or mean of a feature of the weighted signals is calculated to produce a higher quality electromyocardiographic signal. The method and system can also be used to determine signal strength or frequency contents of a signal falling outside the array of electrodes.

This application claims the benefit of the earlier filed InternationalApplication No. PCT/CA00/00808, International Filing Date, 7 Jul. 2000,which designated the United States of America, and which internationalapplication was published under PCT Article 21(2) in English as WOPublication No. WO 01/03579 A1.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a method and system for producing ahigher quality electromyographic signal from signals obtained with anarray of electrodes, in which the electrode-sensed signals are correctedthrough implementation of a weighting function.

2. Brief Description of the Prior Art

The physiological mechanisms which generate myoelectrical activity whena muscle contracts have been known and understood for long time. Inparticular, how to record electromyographic signals from muscles throughan array of electrodes is a well theoretically described topic inphysiology.

Although the theoretical understanding is impressive, thebio-physiological application of this theory is, in practice, stillpartly deficient. As of today, there is known only one standardized andautomatic processing system taking into consideration factors such aselectrode filtering due to changes in the position of the array ofelectrodes relative to the center of the electrically active region ofthe muscle. Application of this technique includes limitations as to itsadaptability to changes in inter-electrode distance and does notoptimize the use of signals available along the electrode array withvarying anatomy and inter-electrode distance.

Also, the prior art technology fails to provide for full correction ofthe signals obtained from electrodes of the array that are notsymmetrically positioned with respect to the center of the electricallyactive region of the muscle.

OBJECTS OF THE INVENTION

An object of the present invention is therefore to overcome the abovedescribed drawback of the prior art by processing the electrode-sensedsignals through a weighting function whose purpose is to correct theseelectrode-sensed signals for a distance separating the electrodes fromthe electrically active region of the muscle.

Another object of the present invention is to predict signals whichcannot be measured through the array of electrodes.

SUMMARY OF THE INVENTION

More particularly, in accordance with the present invention, there isprovided a method of producing a higher quality electromyographic signaldescribing myoelectrical activity of an electrically active region of asubjects muscle, comprising sensing through an array of electrodes aplurality of EMG (electromyogram) signals representative of themyoelectrical activity of the electrically active region of thesubject's muscle, applying a weighting function to the detected EMGsignals and thereby producing weighted signals wherein the weightingfunction contains correction features for the relative locations of theelectrically active region and the electrodes, and combining theweighted signals and thereby producing the higher qualityelectromyographic signal.

The present invention further relates to a system for producing a higherquality electromyographic signal describing myoelectrical activity of anelectrically active region of a subject's muscle, comprising an array ofelectrodes for sensing a plurality of EMG signals representative of themyoelectrical activity of the electrically active region of thesubject's muscle, a weighting filter applied to the detected EMG signalsto produce weighted signals wherein the weighting filter containscorrection features for the relative locations of the electricallyactive region and the electrodes, and a combiner of the weighted signalswherein the combined weighted signals constitute the higher qualityelectromyographic signal.

In accordance with preferred embodiments of the present invention:

-   -   the electrically active region of the subject's muscle comprises        a center, the electrodes are separated from the center of the        electrically active region by respective distances, the        electrodes are separated from each other by an inter-electrode        distance, and the weighting function comprises correction        features for:        -   the relative location of the center of the electrically            active region and the electrodes;        -   the distance separating the center of the electrically            active region and the electrodes;        -   the size of the electrically active region; and        -   the inter-electrode distance;    -   the weighting function comprises correction features for both        cancellation and distance damping effects;    -   the electrically active region of the subject's muscle comprises        a center, the array of electrodes comprises a series of        electrodes with an inter-electrode distance, each EMG signal is        detected through at least two electrodes of the array, and        applying the weighting function comprises:        -   detecting the position of the center of the electrically            active region about the array of electrodes;        -   relating the weighting function to the position of the            center of the electrically active region with respect to the            electrodes of the series;        -   weighting each EMG signal by means of the weighting function            related to the position of the center of the electrically            active region with respect to the electrodes of the series;    -   the series of electrodes has a center and, when the center of        the electrically active region is offset with respect to the        center of the series of electrodes:        -   a larger number of EMG signals are detected by the            electrodes on one side of the center of the electrically            active region than on the other side of that center of the            electrically active region so that EMG signals are missing            on the above mentioned other side; and        -   weigthing of the EMG signals comprises replacing the missing            EMG signals on the said other side by corresponding EMG            signals from the said one side, and subsequently weighting            the replacement EMG signals;    -   combining the weighted signals comprises adding a feature of the        weighted signals together or calculating a mean of a feature of        the weighted signals;    -   the method and system further comprise, prior to combining the        weighted signals, evaluating electromyographic quality of the        weighted signals;    -   evaluating electromyographic quality comprises applying to the        weighted signals quality indexes for detection of at least one        of the following parameters:        -   signal-to-noise ratio;        -   maximum-to-minimum drop in power density;        -   power spectrum deformation;        -   electrical activity related to electrocardiogram/esophageal            peristalsis;    -   evaluating electromyographic quality comprises adding to each        other two of the weighted signals detected through respective        electrodes situated on opposite sides of the center of the        electrically active region to produce a corresponding addition        signal, subtracting these two weighted signals from each other        to produce a corresponding subtraction signal, and comparing        these addition and substration signals, this comparison being        representative of the electromyographic quality of the weighted        signals;    -   the method and system further comprise, prior to combining the        weighted signals, replacing the weighted signals whose evaluated        quality is insufficient; and    -   the method and system comprise replacing the weighted signals        whose evaluated quality is insufficient either by predicted        values or by a last value of the weighted signals considered as        containing electromyographic information; and    -   the method and system comprise replacing the higher quality        electromyographic signal in response to weighted signals of        insufficient quality.

The objects, advantages and other features of the present invention willbecome more apparent upon reading of the following non restrictivedescription of a preferred embodiment thereof, given by way of exampleonly with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

In the appended drawings:

FIG. 1 is a schematic representation of a set-up of an EMG analysissystem;

FIG. 2 is a section of oesophageal catheter on which an array ofelectrodes of the EMG analysis system of FIG. 1 is mounted;

FIG. 3 is a graph showing a set of EMG signals of the diaphragm (EMGdisignals) detected by pairs of successive electrodes of the array of FIG.2;

FIG. 4 is a flow chart illustrating the operation of a preferredembodiment of the method and system according to the invention, forproducing a higher quality electromyographic signal describing themyoelectrical activity of a muscle;

FIG. 5 is a graph showing the distribution of correlation coefficientscalculated for determining the position of the center of an electricallyactive region (EARdi center) of the diaphragm of a subject along thearray of electrodes of FIG. 2;

FIG. 6 is a schematic diagram illustrating the concept embodied by themethod and system according to the present invention;

FIG. 7 illustrates an exemplary weighting function related to the EMGdisignals collected through the array of electrodes of FIG. 2;

FIG. 8 a is a first graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the electrode array symmetrically overlies theEARdi center and the EARdi center is centered between a pair ofelectrodes;

FIG. 8 b is a second graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the electrode pair is shifted with respect tothe EARdi center by a distance smaller than 0.5 inter-electrodedistance, and the EARdi center is located between the electrodes of thecentral pair of the electrode array;

FIG. 8 c is a third graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the array is shifted with respect to the EARdicenter by a distance equal to 0.5 inter-electrode distance and the EARdicenter overlies an electrode common to both the central electrode pairand another adjacent electrode pair;

FIG. 8 d is a fourth graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the array is shifted with respect to the EARdicenter by a distance between 0.5 and 1.5 inter-electrode distance;

FIG. 8 e is a fifth graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the array is shifted with respect to the EARdicenter but the EARdi center is centered between a pair of electrodes asin FIG. 8 a, and two missing EMGdi signals are predicted;

FIG. 8 f is a sixth graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the array is shifted with respect to the EARdicenter by a distance smaller then 0.5 inter-electrode distance as inFIG. 8 b, the EARdi center is located but not centered between a pair ofelectrodes, and two missing EMGdi signals are predicted;

FIG. 8 g is a seventh graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the array is shifted with respect to the EARdicenter the EARdi center overlies an electrode of the array as in FIG. 8c, and two missing EMGdi signals are predicted;

FIG. 9 is a graph showing measured and predicted electrode filteringeffects along an array of electrodes such as that shown in FIG. 2;

FIG. 10 is another graph showing measured electrode filtering effectsalong an array of electrodes comprising overlapping pairs of electrodes;

FIG. 11 is a further graph showing measured electrode filtering effectsalong the array of electrodes of FIG. 2 for an inter-electrode distanceof 5 mm; and

FIG. 12 is still further a graph showing measured electrode filteringeffects along the array of electrodes of FIG. 2 for an inter-electrodedistance of 10 mm.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Electromyographic signals produced by a muscle can be detected by meansof an array of electrodes passing through the center of the muscleelectrically active region. The EMG signals detected through theelectrodes comprise electromyographic and noise components, and theposition of the center of the electrically active region of the musclecan be detected through a reversal of polarity of the electromyographiccomponents of the electrode-sensed EMG signals provided that thepolarity of the electrode pairs is consistent from one end to the otherof the electrode array.

Although the preferred embodiment of the present invention will bedescribed in relation to an electromyographic signal produced by thediaphragm of a subject, it should be kept in mind that it is within thescope of the present invention to process a signal representative of themyoelectrical activity of a muscle other than the diaphragm.

According to the preferred embodiment of the present invention,myoelectrical activity of the diaphragm 11 of a human subject 14 ismeasured through an array of electrodes such as 12 (FIGS. 1 and 2)mounted on the free end section 15 of an oesophageal catheter 13. Asbetter illustrated in FIG. 2, the electrodes 12 are separated by aninter-electrode distance d. FIG. 1 shows that the catheter 13 isintroduced into the subject's oesophagus through one nostril or themouth until the array of electrodes 12 is situated at the level of thegastroesophageal junction.

An electrode 12 can be mounted on the free end section 15 of thecatheter 13 by winding stainless steel wire (not shown) around thatcatheter 13. The wound stainless steel wire presents a rough surfacesmoothed out by solder, which in turn is electroplated with nickel,copper and then gold or silver. Of course, it is within the scope of thepresent invention to use other electrode structures. Also, theelectrodes 12 can possibly be applied to a nasogastric feeding tube (notshown) which is routinely introduced in intensive-care unit (ICU)patients.

Electric wires (not shown) interconnect each pair of successiveelectrodes such as 1-7 (FIG. 2) with a respective one of a group ofdifferential amplifiers 16. Obviously, these electric wires follow thecatheter 13 from the respective electrodes 12 to the correspondingamplifiers 16, and are preferably integrated to the catheter 13.Preferably, the electric wires transmitting the EMGdi signals (EMGsignals from the diaghragm) collected by the various pairs 1-7 ofelectrodes 12 are shielded to reduce the influence of external noise, inparticular disturbance from the 50 or 60 Hz current and voltage of theelecric mains.

The group of differential amplifiers 16 amplifies and bandpass fiberseach EMGdi signal. This subtraction step can also be carried out in thepersonal computer 19 when the amplifiers 16 are single-ended orequivalently designed amplifiers (monopolar readings).

In the example illustrated in FIGS. 1 and 2, the free end section 15 ofthe catheter 13 is provided with an array of eight electrodes 12defining seven pairs 1, 2, 3, 4, 5, 6 and 7 of successive electrodes 12respectively collecting seven different EMGdi signals. Although it hasbeen found that myoelectrical activity of the diaphragm can be measuredaccurately with an oesophageal catheter 13 provided on the free endsection 15 thereof with an array of eight electrodes 12, a differentnumber and/or configuration of pairs of electrodes 12 can becontemplated depending on the subject's anatomy and movement of thediaphragm. Also, the pairs 1-7 do not need to be pairs of successiveelectrodes; they can be overlapping pairs of electrodes or can presentany other configuration of electrode pairs.

A major problem in recording EMGdi signals is to maintain the noiselevel as low and as constant as possible. Since the electric wirestransmitting the EMGdi signals from the electrodes 12 to thedifferential amplifiers 16 act as an antenna, it is crucial, asindicated in the foregoing description, to shield these electric wiresto thereby protect the EMGdi signals from additional artifactual noise.Also, the package enclosing the differential amplifiers 16 is preferablymade as small as possible (miniaturized) and is positioned in closeproximity to the subjects nose to decrease as much as possible thedistance between the electrodes 12 and the amplifiers 16.

The amplified EMGdi signals are sampled by a personal computer 19through respective isolation amplifiers of a unit 18, to form signalsegments of fixed duration. Unit 18 supplies electric power to thevarious electronic components of the differential and isolationamplifiers while ensuring adequate isolation of the subject's body fromsuch power supply. The unit 18 also incorporates bandpass filtersincluded in the respective EMGdi signal channels to eliminate theeffects of aliasing. The successive EMGdi signal segments are thendigitally processed into the personal computer 19 afteranalog-to-digital conversion thereof. This analog-to-digital conversionis conveniently carried out by an analog-to-digital converterimplemented in the personal computer 19. The personal computer 19includes a monitor 40 and a keyboard 31.

It is believed to be within the capacity of those of ordinary skilled inthe art to construct suitable differential amplifiers 16 and an adequateisolation amplifiers and power supply unit 18. Accordingly, theamplifiers 16 and the unit 18 will not be further described in thepresent specification.

An example of te seven EMGdi signals collected by the pairs 1-7 ofsuccessive electrodes 12 (FIGS. 1 and 2) and supplied to the computer 19is illustrated in FIG. 3.

Step 401:

The first operation (step 401 of FIG. 4) performed by the computer 19 isa filtering operation to remove from all the EMGdi signals of FIG. 3electrode motion artifacts, cardiac activity, electrical activityrelated to esophageal peristalsis, 50 and 60 Hz interference from theelectric network, and high frequency noise. Implementation of suchfiltering is believed to be within the capacity of those of ordinaryskill in the art and, accordingly, will not be further described.

Steps 402 and 403:

As the diaphragm is generally perpendicular to the longitudinal axis ofthe oesophageal catheter 13 equipped with an array of electrodes 12,only a portion of the electrodes 12 are situated in the vicinity of thediaphragm. It is therefore important to determine the position of thediaphragm with respect to the oesophageal electrode array. Also thediaphragm moves during breathing and the method and system according tothe invention accounts for this movement of the diaphragm.

The portion of the crural diaphragm 11 which forms the muscular tunnelthrough which the oesophageal catheter 13 is passed is referred to the“diaphragm electrically active region” (EARdi). The thickness of theEARdi is 20-30 mm. It can be assumed that, within the EARdi, thedistribution of active muscle fibers has a center from which themajority of the EMGdi signals originate, i.e. the “diaphragmelectrically active region center” (EARdi center). Therefore, when thepolarity of the recordings is consistent from one end of the electrodearray to the other, EMGdi signals detected on opposite sides of theEARdi center will be reversed in polarity with no phase shift; in otherwords, EMGdi signals obtained along the electrode array become reversedin polarity at the EARdi center.

Moving centrally from the boundaries of the EARdi, EMGdi power spectrumsprogressively attenuate and enhance in frequency. Reversal of signalpolarity on either side of the electrode pair 4 with the most attenuatedpower spectrum confirms the position from which the EMGdi signalsoriginate, the EARdi center.

Referring to FIG. 4, another function of the computer 19 is to determinethe position of the EARdi center along the array of electrodes 12. TheEARdi center is repeatedly updated, that is re-determined atpredetermined time intervals.

For that purpose, the EMGdi signals are cross-correlated in pairs instep 402 to calculate cross-correlation coefficients r in step 403. Aswell known to those of ordinary skill in the art, cross-correlation is astatistical determination of the phase relationship between two signalsand essentially calculates the similarity between two signals in termsof a correlation coefficient r. A negative correlation coefficient rindicates that the cross-correlated signals are of opposite polarities.

FIG. 5 shows curves of the value of the correlation coefficient r versusthe midpoint between the pairs of electrodes from which the correlatedEMGdi signals originate. In this example, the inter-electrode distanceis 10 mm. Curves are drawn for distances between the correlated pairs ofelectrodes 12 of 5 mm (curve 20). 10 mm (curve 21). 15 mm (curve 22) and20 mm (curve 23). One can appreciate from FIG. 5 that negativecorrelation coefficients r are obtained when EMGdi signals fromrespective electrode pairs situated on opposite sides of the electrodepair 4 are cross-correlated. It therefore appears that the change inpolarity occurs in the region of electrode pair 4, which is confirmed bythe curves of FIG. 3. Accordingly, it can be assumed that the EARdicenter is situated substantially midway between the electrodes 12forming pair 4.

Step 404:

In step 404, the correlation coefficients are systematically compared todetermine the EARdi center. For example, the EARdi center can beprecisely determined by interpolation using a square law based fit ofthe three most negative correlation coefficients of curve 21 obtained bysuccessive cross-correlation of the EMGdi signal segments from eachelectrode pair to the EMGdi signal segments from the second nextelectrode pair. The EARdi center is associated to a pair of electrodes12 to provide a “reference position”. In the illustrated example, theEARdi center is associated to pair 4 of electrodes 12.

As mentioned in the foregoing description, the position of the EARdicenter along the array of electrodes 12 is continuously updated, i.e.re-calculated at predetermined time intervals overlapping or not.

Step 405:

Each EMGdi signal obtained on either side of the EARdi center isprocessed, more specifically multiplied/divided/added/subtracted by aweighting function. More specifically, a given parameter of the EMGdisignal is multiplied/divided/added/subtracted by the weighting function.This given parameter may comprise a feature such as, for example, anamplitude, power, area under the rectified signal, etc.

The weighting function can be derived from a mathematical model capableof adjusting each EMGdi signal in relation to the relative position ofthe array of electrodes 12 with respect to the EARdi center. Theweighting function can also be obtained fromweighting-function-describing data measured on the subject's body, forexample by measuring EMGdi signals along the electrode array withknowledge of the position of the EARdi center. Finally the weightingfunction can be derived from both the mathematical model and theweighting function describing data measured on the subject's body. Also,the processing can be performed in the time domain or in the frequencydomain.

The weighting function contains correction for:

-   -   the relative location of the EARdi center with respect to the        pairs of electrodes through which the EMGdi signals are        obtained;    -   the distance separating the EARdi center from the electrodes;    -   the size of the electrically active region (EARdi) of the        diaphragm; and    -   the inter-electrode distance.

Knowing the position of the center of the electrically active region ofthe diaphragm (EARdi) about the array or electrodes, the mathematicalmodel can produce weighting functions correcting for both cancellationeffects and distance damping effects.

For the purpose of illustrating this concept, let's consider FIG. 6 inwhich wanted signals S from a wanted signal source 601 and disturbancesignals D from disturbances 602 are detected through an array ofelectrodes 603. The array of electrodes comprises N electrodes labeledn, where n=1, 2, 3, 4 . . . N. The array of electrodes does not have tobe linearly arranged; any configuration is possible.

The signal detected through a given electrode n depends on 1 ^(st)) theproperties of the sources 601 and 602 (point sources or line sourceswith particular direction or curved line sources) and 2 ^(nd)) thedistances r_(S)(n) and r_(d)(n), respectively, between the sources 601and 602 and the electrode n. Line source signals display a mixedfrequency and distance dependent damping essentially described bymodified bessel functions while point source signals are dampedinversely proportional to the distance and independent of frequency.

The signal from each electrode is processed through the weightingfunction W(n), which is a weighting filter which may be positive,negative or even equal to zero prior to a summation of all contributions(n=1 to N) to give the output signal.

The following relations describe signal conditioning in the spectraldomain:

the signal u(n) at the given electrode n isu(n)=Sf _(s) [r _(s)(n)]+Df _(d) [r _(d)(n)]  (1)the output signal Out 604 is: $\begin{matrix}{{Out} = {\sum\limits_{n = 1}^{N}\quad{{u(n)}\quad{W(n)}}}} & (2)\end{matrix}$Combining the two equations and rearranging the terms give the followingexpression: $\begin{matrix}{{Out} = {{S{\sum\limits_{n = 1}^{N}\quad{{f_{s}\left\lbrack {r_{s}(n)} \right\rbrack}\quad{W(n)}}}} + {D{\sum\limits_{n = 1}^{N}\quad{{f_{d}\left\lbrack {r_{d}(n)} \right\rbrack}\quad{W(n)}}}}}} & (3)\end{matrix}$where f_(s) and f_(d) are functions describing damping and/or otheralteration (such as interference) to the signal as a function ofdistances r_(s) and r_(d), respectively.

FIG. 7 is a graph illustrating an example of weighting function W(n). Ascan be seen the graph of FIG. 7 relates the weighting function W(n) tothe position of the pairs of electrodes from which the EMGdi signals ofFIG. 3 originate, and the center of the EARdi determined through thecorrelation coefficients r in steps 402-404.

In FIG. 7, curve 701 illustrating the weighting function W(n) shows thatsignals from electrode pairs 1, 2, 3, 4, 5, 6 and 7 are represented byrespective local gain values of the weighting function W(n). The localgain values for all electrode pairs is determined by the position of theEARdi center along the array of electrodes. More specifically, the localgain value of electrode pair 4 is the gain value of curve 701 determinedby the position of the EARdi center itself centered between theelectrodes of pair 4 (see dashed line 702). The local gain value ofelectrode pairs 1, 2, 3, 5, 6 and 7 is the gain value of curve 701 atpositions shifted from the EARdi center by a corresponding number ofinter-electrode distances (see dashed lines 703-708). In the illustratedexample, the signal from electrode pair 1 will be represented by gainvalue 0.05 (dashed line 703), the signal from electrode pair 2 will berepresented by gain value 0.3 (dashed line 704), the signal fromelectrode pair 3 will be represented by gain value 0.9 (dashed line705), the signal from electrode pair 4 will be represented by gain value0.3 (dashed line 702), the signal from electrode pair 5 will berepresented by gain value 0.9 (dashed line 706), the signal fromelectrode pair 6 will be represented by gain value 0.3 (dashed line707), and the signal from electrode pair 7 will be represented by gainvalue 0.05 (dashed line 708).

In general terms, for a good performance, the first term of Equation 3should be maximized and the second term minimized, or depending on theapplication of concern, known filtering strategies should be used tooptimize the spectral distributions of wanted and disturbance signals.The optimization is performed by varying sign, strength, and spectral(complex) contents of the weighting filter W(n). This process can beguided by a priori knowledge of the type of signal source (line, point,etc.) and the corresponding type of damping (modified bessel functions,inverse distance damping, etc.) and/or experimental knowledge of thesignals spectral content.

FIGS. 8 a-8 c are graphs showing the effect of moving the EARdi centeralong the array of electrodes from a position in which the EARdi centeris located centrally between a pair of electrodes to a position in whichthe EARdi center overlies an electrode. These graphs clearly show howthe signal amplitudes along the array of electrodes are affected byalteration of the position of the EARdi center with respect to theelectrode pair 4.

The graph of FIG. 8 a shows the gain values of the weighting functionW(n) associated with the various pairs of electrodes of the array, whenthe center of the electrode array symmetrically overlies the EARdicenter and the EARdi center is centered between the central electrodepair 4. The position of the EARdi center is the same as illustrated inFIG. 7. In FIG. 8 a, electrode filtering is symmetrical and presentscancellation at electrode pair 4.

The graph of FIG. 8 b illustrates the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the array is shifted with respect to the EARdicenter by a distance smaller than 0.5 inter-electrode distance. Morespecifically, in FIG. 8 b, the EARdi center is moved (upwardly in thefigure) by 25% of the inter-electrode distance. In this example, theweighting function is skewed, but there is still some cancellation atelectrode pair 4.

FIG. 8 c is a third graph showing the gain values of a weightingfunction W(n) associated with the various pairs of electrodes of thearray, when the center of the array is shifted with respect to the EARdicenter by a distance equal to 0.5 inter-electrode distance and the EARdicenter is centered on an electrode. The resulting weighting function issymmetrical with no cancellation at electrode pair 4.

The above FIGS. 8 a, 8 b and 8 c show three (3) possible locations ofthe EARdi center relative to an electrode pair centered on the electrodearray. The fourth figure, namely FIG. 8 d, exemplifies the behavior ofthe signals if the EARdi center continues to move over to an adjacentelectrode pair. In this latter case, the gain values are the same as inFIG. 8 b but are reversed.

FIGS. 8 e, 8 f and 8 g show the same positional shifts as in FIGS. 8 a,8 b and 8 c but when the EARdi center is located at electrode pair 2instead of central electrode pair 4. The EMGdi signals corresponding toweighting function gain values W(n+2) and W(n+3) then fall outside ofthe electrode array. The missing weighted signals can then be predictedby using the same EMGdi signal detected at electrode pairs 4 and 3processed through the weighting function. These predicted values arethen used in the calculation for the total signal strength across theelectrode array.

In this preferred embodiment, the electrodes at the bottom of the army(FIGS. 8 e-g) are not used. However, depending on how complex the modelfor prediction and computation is, these signals can also be used. Ifcorrection for signals that fall off the electrode array is notperformed, it is impossible to obtain an accurate estimate of the totalsignal value.

Just a word to mention that the weighting function W(n) of the FIGS. 7and 8 regards conditioning of the amplitude of the EMGdi signal andcorresponds to curve 901 of FIG. 9 (curve of the amplitude of the EMGdisignal in relation to the distance of the electrodes of the pair fromthe EARdi center). The EMGdi signals can also be frequency conditionedby constructing a weighting filter using a curve such as 902 in FIG. 9(curve of the center frequency of the EMGdi signal in relation to thedistance of the electrodes of the pair from the EARdi center). Acombination of frequency and amplitude conditioning can also beimplemented.

FIGS. 10, 11 and 12 are other examples of amplitude and frequencyconditioning curves that can serve as weighting functions W(n).

The curves of FIGS. 9, 10, 11 and 12 are usually experimentallyestablished on a sufficient number of recordings in a subject.

Step 406:

In this step, electromyographic quality of the weighted signals isevaluated.

This evaluation of the electromyographic quality of all the weightedsignals can be performed for their relative electromyographic and noisecomponents. Thus, if preferred, summation of the EMGdi signals(amplitude, area under the curve, power, etc.) along the array ofelectrodes can be limited to signals that contain physiologicalinformation pertaining to the diaphragm. This evaluation of signalscontent can be performed by applying well known signal quality indexesfor detection of signal-to-noise ratio, maximum-to-minimum drop in powerdensity, power spectrum deformation, and/or electrocardiogram/esophagealperistalsis.

This evaluation of signals for their relative electromyographic andnoise components can also be obtained by adding and subtracting EMGdisignals obtained on opposite sides with symmetrical position to theelectrically active region center (for example signals from electrodepairs 3 and 5 in FIG. 7) and comparing the results of these addition andsubtraction. A first EMGdi signal detected by a pair of electrodes ofthe array on a first side of the center of the EARdi has anelectromyographic component of a first polarity and a noise component ofgiven polarity. A second EMGdi signal detected by another pair ofelectrodes of the array on the second side of the EARdi center, oppositeto the first side, has an electromyographic component of a secondpolarity opposite to the first polarity and a noise component of saidgiven polarity. Subtraction of the first and second EMGdi signalssubtracts the noise components of the first and second EMGdi signalsfrom each other but adds the electromyographic components of these firstand second EMGdi signals together to produce a resulting signal withhigh electromyographic content and low noise content. Addition of thefirst and second EMGdi signals adds the noise components of the firstand second EMGdi signals to each other but subtracts theelectromyographic components of these first and second EMGdi signalsfrom each other to produce a signal with low electromyographic contentand high noise content. Comparison of the resulting added and subtractedsignals (area under the curve/power/amplitude of the signals) providesinformation about the relative contribution of noise andelectromyographic content to the signal. Signals with a highelectromyographic content will be considered as a high quality signal.

Step 407:

EMGdi signals considered as not containing physiological information(insufficient quality as determined in step 406) pertaining to thediaphragm can be replaced by predicted values or simply the last valueconsidered to contain physiological information pertaining to thediaphragm. This replacement strategy can be applied on either eachsingle EMGdi signal obtained from the electrode array or on thesummation or mean of the weighted EMGdi signals representative for allor some of the signals obtained along the electrode array.

Step 408:

The last step consists of calculating the sum of a feature (RMS voltage,RMS current, power, RMS means amplitude, area under the curve, etc) ofthe eventually replaced, signal quality evaluated weighted EMGdi signalsfrom the electrodes of the array. A mean of the rectified signals, or aRMS or other suitable or equivalent value of these signals can becalculated as well for further use.

The resulting signal will provide improvement of the signal-to-noiseratio and minimize influence of electrode filtering due to changes inthe position of the electrode array relative the muscle's electricallyactive region center. It also accounts for differences in anatomybetween individuals and differences in inter-electrode distance anddesign, and for the EARdi center approaching the distal or proximal endof the array of electrodes.

Of course, the application of the present invention is not limited tothe diaphragm but to any other muscle and that, for any type of array ofelectrodes.

Although the present invention has been described hereinabove by way ofa preferred embodiment thereof, this embodiment can be modified at will,within the scope of the appended claims, without departing from thespirit and nature of the subject invention.

1. A method of producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: sensing through an array of electrodes a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; applying a weighting function to the detected EMG signals and thereby producing weighted signals, the electrically active region of the subject's muscle comprising a center and the weighting function containing correction features for the relative locations of the center of the electrically active region and the electrodes; and combining the weighted signals and thereby producing the higher quality electromyographic signal.
 2. A method of producing a higher quality electromyographic signal as defined in claim 1, wherein the weighting function comprises correction features for both cancellation and distance damping effects.
 3. A method of producing a higher quality electromyographic signal as defined in claim 1, wherein combining the weighted signals comprises: adding a feature of the weighted signals together.
 4. A method of producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: sensing through an array of electrodes a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; applying a weighting function to the detected EMG signals and thereby producing weighted signals; and combining the weighted signals and thereby producing the higher quality electromyographic signal; wherein: the electrically active region of the subject's muscle comprises a center; the electrodes are separated from the center of the electrically active region by respective distances; the electrodes are separated from each other by an inter-electrode distance; and the weighting function comprises correction features for: the relative location of the center of the electrically active region and the electrodes; the distance separating the center of the electrically active region and the electrodes; the size of the electrically active region; and the inter-electrode distance.
 5. A method of producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: sensing through an array of electrodes a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; applying a weighting function to the detected EMG signals and thereby producing weighted signals, the weighting function containing correction features for the relative locations of the electrically active region and the electrodes; and combining the weighted signals and thereby producing the higher quality electromyographic signal; wherein the electrically active region of the subject's muscle comprises a center, the array of electrodes comprises a series of electrodes with an inter-electrode distance, each EMG signal is detected through at least two electrodes of the array, and wherein applying the weighting function comprises: detecting the position of the center of the electrically active region about the array of electrodes; relating the weighting function to the position of the center of the electrically active region with respect to the electrodes of said series; weighting each EMG signal by means of the weighting function related to the position of the center of the electrically active region with respect to the electrodes of said series.
 6. A method of producing a higher quality electromyographic signal as defined in claim 5, wherein the series of electrodes has a center, and wherein, when the center of the electrically active region is offset with respect to the center of the series of electrodes: a larger number of EMG signals are detected by the electrodes on one side of the center of the electrically active region than on the other side of said center of the electrically active region so that EMG signals are missing on said other side; and weigthing of the EMG signals comprises replacing the missing EMG signals on said other side by corresponding EMG signals from said one side and subsequently weighting said replacement EMG signals.
 7. A method of producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: sensing through an array of electrodes a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; applying a weighting function to the detected EMG signals and thereby producing weighted signals, the weighting function containing correction features for the relative locations of the electrically active region and the electrodes; and combining the weighted signals and thereby producing the higher quality electromyographic signal, wherein combining the weighted signals comprises calculating a mean of a feature of the weighted signals.
 8. A method of producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: sensing through an array of electrodes a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; applying a weighting function to the detected EMG signals and thereby producing weighted signals, the weighting function containing correction features for the relative locations of the electrically active region and the electrodes; and combining the weighted signals and thereby producing the higher quality electromyographic signal; wherein said method of producing a higher quality electromyographic signal further comprises, prior to combining the weighted signals, evaluating electromyographic quality of the weighted signals.
 9. A method of producing a higher quality electromyographic signal as recited in claim 8, wherein evaluating electromyographic quality comprises applying to the weighted signals quality indexes for detection of at least one of the following parameters: signal-to-noise ratio; maximum-to-minimum drop in power density; power spectrum deformation; electrical activity related to electrocardiogram/esophageal peristalsis.
 10. A method of producing a higher quality electromyographic signal as recited in claim 8, wherein the electrically active region of the subject's muscle comprises a center, and wherein evaluating electromyographic quality comprises adding to each other two of the weighted signals detected through respective electrodes situated on opposite sides of the center of the electrically active region to produce a corresponding addition signal, subtracting said two weighted signals from each other to produce a corresponding subtraction signal, and comparing said addition and subtraction signals, said comparison being representative of the electromyographic quality of the weighted signals.
 11. A method of producing a higher quality electromyographic signal as recited in claim 8, further comprising, prior to combining the weighted signals, replacing the weighted signals whose evaluated quality is insufficient.
 12. A method of producing a higher quality electromyographic signal as recited in claim 11, comprising replacing the weighted signals whose evaluated quality is insufficient by predicted values.
 13. A method of producing a higher quality electromyographic signal as recited in claim 11, comprising replacing the weighted signals whose evaluated quality is insufficient by a last value of said weighted signals considered as containing electromyographic information.
 14. A method of producing a higher quality electromyographic signal as recited in claim 8, comprising replacing the higher quality electromyographic signal in response to weighted signals of insufficient quality.
 15. A system for producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: an array of electrodes for sensing a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; a weighting filter applied to the detected EMG signals to produce weighted signals, the electrically active region of the subject's muscle comprising a center and the weighting filter containing correction features for the relative locations of the center of the electrically active region and the electrodes; and a combiner of the weighted signals, the combined weighted signals constituting the higher quality electromyographic signal.
 16. A system for producing a higher quality electromyographic signal as defined in claim 15, wherein the weighting filter comprises correction features for both cancellation and distance damping effects.
 17. A system for producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: an array of electrodes for sensing a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; a weighting filter applied to the detected EMG signals to produce weighted signals, the weighting filter containing correction features for the relative locations of the electrically active region and the electrodes; and a combiner of the weighted signals, the combined weighted signals constituting the higher quality electromyographic signal; wherein: the electrically active region of the subject's muscle comprises a center; the electrodes are separated from the center of the electrically active region by respective distances; the electrodes are separated from each other by an inter-electrode distance; and the weighting filter comprises correction features for: the relative location of the center of the electrically active region and the electrodes; the distance separating the center of the electrically active region and the electrodes; the size of the electrically active region; and the inter-electrode distance.
 18. A system for producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: an array of electrodes for sensing a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; a weighting filter applied to the detected EMG signals to produce weighted signals, the weighting filter containing correction features for the relative locations of the electrically active region and the electrodes; and a combiner of the weighted signals, the combined weighted signals constituting the higher quality electromyographic signal; wherein: the electrically active region of the subject's muscle comprises a center; the array of electrodes comprises a series of electrodes with an inter-electrode distance; each EMG signal is detected through at least two electrodes of the array; and the weighting filter comprises a weighting function related to the position of the center of the electrically active region with respect to the electrodes of said series.
 19. A system for producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: an array of electrodes for sensing a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; a weighting filter applied to the detected EMG signals to produce weighted signals, the weighting filter containing correction features for the relative locations of the electrically active region and the electrodes; and a combiner of the weighted signals, the combined weighted signals constituting the higher quality electromyographic signal; wherein the series of electrodes has a center, wherein the electrically active region of the subject's muscle has a center, and wherein, when the center of the electrically active region is offset with respect to the center of the series of electrodes: a larger number of EMG signals are detected by the electrodes on one side of the center of the electrically active region than on the other side of said center of the electrically active region so that EMG signals are missing on said other side; and the system comprises means for replacing the missing EMG signals on said other side by corresponding EMG signals from said one side, and means for subsequently weighting said replacement EMG signals.
 20. A system for producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: an array of electrodes for sensing a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; a weighting filter applied to the detected EMG signals to produce weighted signals, the weighting filter containing correction features for the relative locations of the electrically active region and the electrodes; and a combiner of the weighted signals, the combined weighted signals constituting the higher quality electromyographic signal; wherein the combiner comprises: an adder of a feature of the weighted signals.
 21. A system for producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: an array of electrodes for sensing a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; a weighting filter applied to the detected EMG signals to produce weighted signals, the weighting filter containing correction features for the relative locations of the electrically active region and the electrodes; and a combiner of the weighted signals, the combined weighted signals constituting the higher quality electromyographic signal; wherein the combiner comprises: a calculator of a mean of a feature of the weighted signals.
 22. A system for producing a higher quality electromyographic signal describing myoelectrical activity of an electrically active region of a subject's muscle, comprising: an array of electrodes for sensing a plurality of EMG signals representative of the myoelectrical activity of the electrically active region of the subject's muscle; a weighting filter applied to the detected EMG signals to produce weighted signals, the weighting filter containing correction features for the relative locations of the electrically active region and the electrodes; and a combiner of the weighted signals, the combined weighted signals constituting the higher quality electromyographic signal; wherein said system for producing a higher quality electromyographic signal further comprises, prior to combining the weighted signals, an evaluator of an electromyographic quality of the weighted signals.
 23. A system for producing a higher quality electromyographic signal as recited in claim 22, wherein the evaluator comprises means for applying to the weighted signals quality indexes for detection of at least one of the following parameters: signal-to-noise ratio; maximum-to-minimum drop in power density; power spectrum deformation; electrical activity related to electrocardiogram/esophageal peristalsis.
 24. A system for producing a higher quality electromyographic signal as recited in claim 22, wherein the electrically active region of the subject's muscle comprises a center, and wherein the evaluator comprises an adder of two of the weighted signals detected through respective electrodes situated on opposite sides of the center of the electrically active region to produce a corresponding addition signal, a subtractor of said two weighted signals from each other to produce a corresponding subtraction signal, and a comparator of said addition and subtraction signals, this comparison being representative of the electromyographic quality of the weighted signals.
 25. A system for producing a higher quality electromyographic signal as recited in claim 22, further comprising means for replacing, prior to combining the weighted signals, the weighted signals whose evaluated quality is insufficient.
 26. A system for producing a higher quality electromyographic signal as recited in claim 25, comprising means for replacing the weighted signals whose evaluated quality is insufficient by predicted values.
 27. A system for producing a higher quality electromyographic signal as recited in claim 25, comprising means for replacing the weighted signals whose evaluated quality is insufficient by a last value of said weighted signals considered as containing electromyographic information.
 28. A system for producing a higher quality electromyographic signal as recited in claim 22, comprising means for replacing the higher quality electromyographic signal in response to weighted signals of insufficient quality. 